LLM Fine-Tuning Course – From Supervised FT to RLHF, LoRA, and Multimodal
This course, developed by Sunonny Sevita, offers a comprehensive guide to fine-tuning large language models (LLMs) using advanced techniques and practical tools, essential for understanding LLMs and excelling in AI or ML roles.
MAIN POINTS FROM TRANSCRIPT
- Course covers supervised fine-tuning and advanced alignment techniques like RLHF and DPO.
- Hands-on practice with Hugging Face, Unsloth, and Axelottle for technical proficiency.
- Focus on parameter-efficient strategies such as Laura and Qura.
- Includes practical implementation of SLM, multimodal, and embedding fine-tuning.
TAKEAWAYS
- Gain deep understanding of LLM training pipelines and fine-tuning processes.
- Learn to align AI models with human preferences through practical examples.
- Explore differences between frameworks like Hugging Face and Llama Factory.
- Enhance skills for AI and ML interviews with structured, practical content.